How Companies Translate Big Data Into Business Intelligence

2 April 2016

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In today’s business environment, companies are increasingly making decisions based on Big Data. It has gone from being a buzzword that was associated with tech giants like Google and Facebook to every industry (both big and small). With large volumes of data pouring in, businesses need to develop protocols to manage the massive amount of structured and unstructured data.

All the data in the world is useless unless you know how to efficiently analyze it.

By conducting a proper analysis, Big Data can be used to perform the following tasks:

Identify trends

Detect patterns

Collect other valuable data

Although it may sound easy enough, performing analysis of Big Data is not an easy task. An out of the box Big Data analytics software will not be a solution perfectly suited to your business. As a result, any Big Data analysis starts with thorough planning with professionals that have the right skillset.

In the past few years, the process of gathering data has improved drastically and executives at all levels have realized the importance of Big Data. Staying competitive in the market and growing your customer base is all dependent on Big Data. With huge amounts of data being collected by various businesses on multiple platforms, touchpoints, devices, and offline the focus is now slowly changing to access, control, and visualization of this data. This in turn also monetizes the audience in real-time which is the key reason why new terms like customer data platforms and predictive analytics are becoming common.

According to Forbes, companies will spend approximately $7.4 billion over year on data-driven projects. Further, 80% of enterprises will invest about 13.8 million and 63% of small to medium size businesses will invest approximately $1.6 million on Big Data analytics.

Big Data Market Trends

It’s all about Data Agility

With the Internet of Things (IoT), data will keep pouring in from multiple sources. It’s pointless to own a vast amount of data if it’s not agile. So companies are trying to develop ways to simplify the process so that the customer data can be safely used across various departments. Further, the information needs to be saved on several legacy platforms and third-party vendor systems. As a result it makes agility all the more challenging making it a top business priority.

It’s all about owning the data

A lot of businesses have realized the benefits of owning and controlling the information. Working with third-party vendors can be a frustrating way to gather data and gaining rights to this data can also be a nightmare. As a result, companies have started creating new technology to enable them to gather first-party customer data (online, offline, platforms and sellers) to possess and unify the data. This enables businesses to maximize the use of the data optimizing their sales and marketing efforts in real-time.

Customer information platforms have started to take center stage

In order to simplify the Big Data analytics process, companies are pursuing a unified customer database. At the present time, there are still many businesses operating multiple platforms and systems, however this practice of collecting data separately will come to end soon. With cost-effective tools like Apache Spark added to the mix, this phenomenon will become increasingly important.

Big Data has been democratized across the board

In the past, only corporate giants had access to this data, but now it has become easier and cheaper for companies to gather their own data and build customer databases both online and offline (and engage in analytics).

How Are Brands Using Big Data?

By incorporating Big Data analytics, data-driven enterprises are able to better understand issues in order to increase productivity, cut costs, grow their market share, make maximum use of resources, gain customer insights, and develop accurate pricing and forecasting models.

For example, UPS used Big Data analytics to cut down 2.3 million miles from its routes. This in turn reduced engine idle time by approximately 10 million minutes, reduced carbon emission by approximately 6,500 metric tons, and saved 650,000 gallons of fuel.

Further, the pharmaceutical company Express Scripts used their patient information to accurately predict the patients who were likely to forget to order a refill of their medication. This enabled them to add customized reminders on-pill bottle-caps making the system more efficient and save lives.

According to a survey conducted by Teradata Corp., Big Data is significantly shaping business by driving opportunities and innovation like developing new business models, finding new product offers, and monetizing data by selling it to external companies.

Supermarket chains like the British giant Tesco now saves about 100 million pounds of food from being wasted every year. This is how incredible it can be if you incorporate predictive analysis to the information you have collected. Further, the department store Macy’s now adjusts pricing on 73 million products in real-time based on inventory and demand.

As a result, it’s plain to see that Big Data opens the doors to a wide array of possibilities and new opportunities. Without properly studying the data, businesses can be sideswiped by not identifying market and business trends sooner.

At the same time there will be more security and privacy challenges to overcome. However, government legislation will further set up the guidelines, but Big Data is not going away.

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Andrew is our IT storyteller and copywriter. His current undertaking is big data analytics and CSS as well as digital design and branding.
He is a contributor to various publications with a focus on new technology and marketing.

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